阅读说明：本技术 一种6g移动通信卫星地面网分布式资源分配方法 (Distributed resource allocation method for 6G mobile communication satellite ground network ) 是由 许海涛 林福宏 周贤伟 于 2021-07-15 设计创作，主要内容包括：本发明提供一种6G移动通信卫星地面网分布式资源分配方法,属于移动通信技术领域。所述方法包括：构建一个由多颗卫星和多个移动用户组成的6G移动通信卫星地面网；将6G移动通信卫星地面网中所有卫星分为从移动用户获得服务需求的猎物卫星和从猎物卫星中获取服务负载的捕食者卫星；基于Lotka-Volterra模型,分别构建猎物卫星和捕食者卫星服务负载动态变化函数来描述不同卫星间的负载平衡问题；对构建的猎物卫星和捕食者卫星服务负载动态变化函数进行求解,达到猎物卫星和捕食者卫星之间的负载均衡。采用本发明,能够实现猎物卫星和捕食者卫星之间的负载均衡以及通信网络资源的有效分配。(The invention provides a distributed resource allocation method for a 6G mobile communication satellite ground network, belonging to the technical field of mobile communication. The method comprises the following steps: constructing a 6G mobile communication satellite ground network consisting of a plurality of satellites and a plurality of mobile users; dividing all satellites in a 6G mobile communication satellite ground network into prey satellites for acquiring service requirements from mobile users and predator satellites for acquiring service loads from the prey satellites; based on a Lotka-Volterra model, constructing a prey satellite and predator satellite service load dynamic change function respectively to describe the load balance problem among different satellites; and solving the constructed dynamic change function of the service load of the prey satellite and the predator satellite to achieve load balance between the prey satellite and the predator satellite. By adopting the method and the system, the load balance between the prey satellite and the predator satellite and the effective allocation of communication network resources can be realized.)

1. A distributed resource allocation method for a 6G mobile communication satellite ground network is characterized by comprising the following steps:

constructing a 6G mobile communication satellite ground network consisting of a plurality of satellites and a plurality of mobile users;

dividing all satellites in a 6G mobile communication satellite ground network into prey satellites for acquiring service requirements from mobile users and predator satellites for acquiring service loads from the prey satellites;

based on a Lotka-Volterra model, constructing a prey satellite and predator satellite service load dynamic change function respectively to describe the load balance problem among different satellites;

and solving the constructed dynamic change function of the service load of the prey satellite and the predator satellite to achieve load balance between the prey satellite and the predator satellite.

2. The distributed resource allocation method for the ground network of the 6G mobile communication satellite according to claim 1, wherein the constructing of the prey satellite service load dynamic variation function based on the Lotka-Volterra model comprises:

determining a dynamic change function of the service load of the prey satellite when unloading does not occur based on a Lotka-Volterra model;

determining a dynamic change function of prey satellite service offloading in the event of offloading when the computational power of the predator satellite is less than the offloading rate of the prey satellite service load based on the determined dynamic change function of the prey satellite service load when offloading does not occur;

according to the internal influence of the satellite group, a dynamic change function of the service load of the prey satellite under the unloading occurrence condition is restated;

and adding the interference of the external random factors to the dynamic change function of the game satellite service load after the restated to obtain the dynamic change function of the game satellite service load under the interference of the external random factors.

3. The method of claim 2 wherein the dynamic change function of the service load of the prey satellite without offloading is expressed as:

wherein x is₁(t) shows prey satellite s at time t₁Service load on, a₁(t) denotes prey satellite s₁Rate of change of service load, u₁(t) denotes prey satellite s₁The act of attracting mobile subscribers to the satellite network, ∈₁Is the relevant weighting parameter used to represent the conversion percentage.

4. The distributed resource allocation method for ground network of 6G mobile communication satellite according to claim 3, wherein when the computational power of the predator satellite is lower than the offloading rate of the service load of the prey satellite, the dynamic variation function of the service offloading of the prey satellite in case of offloading occurring is expressed as:

wherein, b₁Representing satellite s from prey₁To predator satellite s₂Of the service load, x₂(t) denotes the predator satellite s at time t₂The service load on the mobile terminal.

5. The method of claim 4 wherein the dynamically changing function of the restated ground network for the game satellite service load is expressed as:

wherein, c₁Representing factors of influence within the constellation of satellites.

6. The distributed resource allocation method for ground network of 6G mobile communication satellite according to claim 5, wherein the dynamic variation function of the service load of the prey satellite under the interference of external random factors is expressed as:

dx₁(t)＝x₁(t)[a₁(t)-b₁x₂(t)-c₁x₁(t)+ε₁u₁(t)]dt+σ₁(t)x₁(t)dB₁(t)

wherein σ₁(t) weighting parameter representing interference of external random factors, B₁(t) represents the distribution function of the external random factor interference.

7. The distributed resource allocation method for the terrestrial network for 6G mobile communication satellites according to claim 1, wherein the constructing a predator satellite service load dynamic variation function based on the Lotka-Volterra model comprises:

determining a dynamic change function of the service load of the predator satellite when unloading does not occur based on a Lotka-Volterra model;

determining a dynamic change function of predator satellite service offloading in the event of offloading when the computational power of the predator satellite is less than the offloading rate of the prey satellite service load based on the determined dynamic change function of the predator satellite service load when offloading is not occurring;

according to the internal influence of the satellite group, a dynamic change function of the predator satellite service load under the unloading condition is restated;

and adding the interference of the external random factors to the dynamic change function of the predator satellite service load after the restated expression to obtain the dynamic change function of the predator satellite service load under the interference of the external random factors.

8. The method of claim 7 wherein the dynamically changing function of the service load of the predator satellite without offloading is expressed as:

wherein x is₂(t) denotes the predator satellite s at time t₂Service load on, a₂(t) predator satellites s₂Rate of change of service load, u₂(t) predator satellites s₂The act of attracting mobile subscribers to the satellite network, ∈₂Is the relevant weighting parameter used to represent the conversion percentage;

when the computational power of a predator satellite is lower than the unload rate of the prey satellite service load, the dynamic change function of predator satellite service unloading in the event of unloading is expressed as:

wherein x is₁(t) shows prey satellite s at time t₁Service load on, b₂Representing satellite s from prey₁To predator satellite s₂The rate of increase in service load caused by the offloading process.

9. The method of claim 8 wherein the dynamically changing function of the restated predator satellite service load is expressed as:

wherein, c₂Representing factors of influence within the constellation of satellites.

10. The distributed resource allocation method for terrestrial networks over 6G mobile communications satellites according to claim 9, wherein the dynamic variation function of the predator satellite service load under external random factor interference is expressed as:

dx₂(t)＝x₂(t)[-a₂(t)+b₂x₁(t)-c₂x₂(t)+ε₂u₂(t)]dt+σ₂(t)x₂(t)dB₂(t)

wherein σ₂(t) a weighting parameter representing interference of an external random factor; b is₂(t) represents the distribution function of the external random factor interference.

Technical Field

The invention relates to the technical field of mobile communication, in particular to a distributed resource allocation method for a 6G mobile communication satellite ground network.

Background

With the development of internet technology, logistics transportation, material exploration and the vigorous development of digital cities, higher data communication requirements and more accurate position information become main characteristics of the information era. Relying solely on terrestrial mobile networks cannot withstand the enormous impact of data volume. In view of the rapid change of the ground terminal facilities and the satellite networking in recent years, with the rapid development of the technology, the satellite network has great advantages in round trip delay and coverage performance, and can provide a wide range of coverage and telecommunication. Therefore, the combined establishment of a satellite ground depth integrated network by a large-capacity ground mobile communication network is an effective way to solve the problem and is also an important direction for the development of the future 6G communication. Through increasingly perfect wide area coverage of ground networks and space-based networks, the ideas of 6G ubiquitous connection and holographic links can be effectively realized.

However, the convergence of cellular mobile networks with satellite communication networks is facing serious challenges. For terrestrial cellular networks, there is a serious imbalance in resource allocation for small-scale cellular networks as the coverage of 5G networks and mobile terminal mobility improve. In a satellite communication network scenario, a certain end-to-end communication delay is caused by a complex deep space environment and a complex satellite network topology. In addition, satellite network traffic is unevenly distributed in consideration of the regional problem of coverage density of the existing satellite network and the problem of communication demand and service distribution in the actual region. These factors can cause network congestion in a local area of the satellite network, while network resources in a portion of the area are idle.

For the above problems, the traditional routing algorithm of the communication network is no longer applicable, and the reduction of the number of congested links by the load balancing algorithm needs to be considered, so as to realize effective network load balancing. In a communication network, a load balancing technology is to transfer overloaded node services to underloaded nodes when the network is congested, so as to realize balanced distribution of the services. The traditional load balancing routing algorithm is passively triggered, that is, load balancing is performed only when congestion occurs, so as to save processing resources. However, it does not provide effective service support in the face of the current huge data communication needs and fast and efficient traffic processing needs.

Disclosure of Invention

The embodiment of the invention provides a distributed resource allocation method for a ground network of a 6G mobile communication satellite, which can realize load balance between a prey satellite and a predator satellite. The technical scheme is as follows:

the embodiment of the invention provides a distributed resource allocation method for a 6G mobile communication satellite ground network, which comprises the following steps:

constructing a 6G mobile communication satellite ground network consisting of a plurality of satellites and a plurality of mobile users;

dividing all satellites in a 6G mobile communication satellite ground network into prey satellites for acquiring service requirements from mobile users and predator satellites for acquiring service loads from the prey satellites;

based on a Lotka-Volterra model, constructing a prey satellite and predator satellite service load dynamic change function respectively to describe the load balance problem among different satellites;

and solving the constructed dynamic change function of the service load of the prey satellite and the predator satellite to achieve load balance between the prey satellite and the predator satellite.

Further, based on the Lotka-Volterra model, constructing a prey satellite service load dynamic change function comprises:

determining a dynamic change function of the service load of the prey satellite when unloading does not occur based on a Lotka-Volterra model;

determining a dynamic change function of prey satellite service offloading in the event of offloading when the computational power of the predator satellite is less than the offloading rate of the prey satellite service load based on the determined dynamic change function of the prey satellite service load when offloading does not occur;

according to the internal influence of the satellite group, a dynamic change function of the service load of the prey satellite under the unloading occurrence condition is restated;

and adding the interference of the external random factors to the dynamic change function of the game satellite service load after the restated to obtain the dynamic change function of the game satellite service load under the interference of the external random factors.

Further, the dynamic change function of the service load of the prey satellite when no offloading occurs is expressed as:

wherein x is₁(t) shows prey satellite s at time t₁Service load on, a₁(t) denotes prey satellite s₁Rate of change of service load, u₁(t) denotes prey satellite s₁The act of attracting mobile subscribers to the satellite network, ∈₁Is the relevant weighting parameter used to represent the conversion percentage.

Further, when the computational power of predator satellites is lower than the offloading rate of the prey satellite service load, the dynamic variation function of the prey satellite service offloading in the case of offloading occurring is expressed as:

wherein, b₁Representing satellite s from prey₁To predator satellite s₂Of the service load, x₂(t) denotes the predator satellite s at time t₂The service load on the mobile terminal.

Further, the restated dynamic change function of the service load of the prey satellite is expressed as:

wherein, c₁Representing factors of influence within the constellation of satellites.

Further, the dynamic change function of the service load of the prey satellite under the interference of the external random factors is expressed as:

dx₁(t)＝x₁(t)[a₁(t)-b₁x₂(t)-c₁x₁(t)+ε₁u₁(t)]dt+σ₁(t)x₁(t)dB₁(t)

wherein σ₁(t) denotes an external followerWeighting parameters of machine-factor interference, B₁(t) represents the distribution function of the external random factor interference.

Further, constructing a predator satellite service load dynamic change function based on the Lotka-Volterra model comprises:

determining a dynamic change function of the service load of the predator satellite when unloading does not occur based on a Lotka-Volterra model;

determining a dynamic change function of predator satellite service offloading in the event of offloading when the computational power of the predator satellite is less than the offloading rate of the prey satellite service load based on the determined dynamic change function of the predator satellite service load when offloading is not occurring;

according to the internal influence of the satellite group, a dynamic change function of the predator satellite service load under the unloading condition is restated;

and adding the interference of the external random factors to the dynamic change function of the predator satellite service load after the restated expression to obtain the dynamic change function of the predator satellite service load under the interference of the external random factors.

Further, the dynamic change function of the predator satellite service load when no offloading has occurred is expressed as:

wherein x is₂(t) denotes the predator satellite s at time t₂Service load on, a₂(t) predator satellites s₂Rate of change of service load, u₂(t) predator satellites s₂The act of attracting mobile subscribers to the satellite network, ∈₂Is the relevant weighting parameter used to represent the conversion percentage;

when the computational power of a predator satellite is lower than the unload rate of the prey satellite service load, the dynamic change function of predator satellite service unloading in the event of unloading is expressed as:

wherein x is₁(t) shows prey satellite s at time t₁Service load on, b₂Representing satellite s from prey₁To predator satellite s₂The rate of increase in service load caused by the offloading process.

Further, the restated predator satellite service load dynamic change function is expressed as:

wherein, c₂Representing factors of influence within the constellation of satellites.

Further, the dynamic variation function of predator satellite service load under external random factor interference is expressed as:

dx₂(t)＝x₂(t)[-a₂(t)+b₂x₁(t)-c₂x₂(t)+ε₂u₂(t)]dt+σ₂(t)x₂(t)dB₂(t)

wherein σ₂(t) a weighting parameter representing interference of an external random factor; b is₂(t) represents the distribution function of the external random factor interference.

The technical scheme provided by the embodiment of the invention has the beneficial effects that at least:

in the embodiment of the invention, a new load balancing model is constructed for a 6G mobile communication satellite ground network, namely a bait-predator-based Lotka-Volterra model is used for constructing a prey satellite and predator satellite service load dynamic change function to describe the load balancing problem among different satellites, and the constructed prey satellite and predator satellite service load dynamic change function is solved to achieve the load balancing between the prey satellite and the predator satellite, so that the effective distribution of communication network resources (specifically, various resources required by providing services for users, such as resources of calculation, communication and the like) is realized, the problem that the existing load balancing algorithm cannot provide effective communication network resource distribution is solved, and the load balancing model has higher data processing efficiency and data transmission rate.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a schematic flow chart of a distributed resource allocation method for a 6G mobile communication satellite ground network according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

As shown in fig. 1, an embodiment of the present invention provides a method for allocating distributed resources in a terrestrial network of a 6G mobile communication satellite, including:

s101, constructing a 6G mobile communication satellite ground network consisting of a plurality of satellites and a plurality of mobile users;

s102, dividing all satellites into prey satellites for obtaining service requirements from mobile users and predator satellites for obtaining service loads from the prey satellites;

s103, respectively constructing a prey satellite and predator satellite service load dynamic change function to describe the load balance problem among different satellites based on a Lotka-Volterra model (specifically: a Lotka-Volterra model based on bait-predators);

and S104, solving the constructed dynamic change function of the service load of the prey satellite and the predator satellite to achieve load balance between the prey satellite and the predator satellite.

The distributed resource allocation method of the 6G mobile communication satellite ground network in the embodiment of the invention constructs a new load balancing model aiming at the 6G mobile communication satellite ground network, even if a bait-predator-based Lotka-Volterra model is used, a prey satellite and predator satellite service load dynamic change function is constructed to describe the load balance problem among different satellites, solving the constructed dynamic change function of the service load of the prey satellite and the predator satellite so as to achieve the load balance between the prey satellite and the predator satellite and realize the effective distribution of communication network resources (particularly various resources required by providing service for users, such as resources of calculation, communication and the like), the method solves the problem that the existing load balancing algorithm cannot provide effective communication network resource allocation, and the load balancing model has higher data processing efficiency and data transmission rate.

In this embodiment, the service load refers to a load amount of a service to be provided.

In this embodiment, the mobile subscriber may request and obtain the 6G mobile communication service from the satellite, and the satellite may provide the 6G mobile communication service for the mobile subscriber. With the development of satellite terrestrial networks, more and more satellites are being utilized to provide access services to mobile users. Different satellites will get different service loads from the mobile user due to their different communication and computing capabilities.

In the embodiment, all the satellites are divided into two groups, and one group of satellites is regarded as a prey satellite and can obtain service requirements from mobile users; the other group of satellites is regarded as predator satellites, and service load can be obtained from prey satellites; wherein the content of the first and second substances,

predator satellites are a group of satellites with strong communication and computing power, which are typically geostationary satellites with high bit rates and high transmission delays. Given the large transmission delays, such satellites cannot provide direct access services to mobile users.

Prey satellites are satellites with limited communication and computing capabilities, all of which are low earth orbit satellites that provide access to mobile subscribers with low transmission delays.

In this embodiment, under the condition of limited communication and computing capabilities, because the capacity of the satellite is limited, the increasing service requirements of the mobile users cannot be met, and part of the service requirements of the mobile users need to be transferred to the satellite with stronger communication and computing capabilities, that is, the prey satellite should unload the service load to the predator satellite.

In a specific embodiment of the foregoing 6G mobile communication satellite ground network distributed resource allocation method, further, constructing a prey satellite service load dynamic change function based on a Lotka-Volterra model includes:

a1, determining a dynamic change function of the service load of the prey satellite when unloading does not occur based on a Lotka-Volterra model;

in this embodiment, assume that the capacity-limited satellite node is s₁The prey satellite represented, the satellite node with the larger capacity is considered as s₂Predator satellites are shown, assuming only prey satellite s₁Can the mobile user be served directly. Predator satellite s₂Can only obtain satellite s from prey₁The offloaded service load. At time t, suppose satellite s is the prey₁Service load of x₁(t) if prey satellite s₁On the service load is not offloaded to predator satellites s₂Above, then based on the Lotka-Volterra model, prey satellites s₁The dynamic change function of the service load when no offloading has occurred can be expressed as:

wherein, a₁(t) denotes prey satellite s₁Rate of change of service load, u₁(t) denotes prey satellite s₁The act of attracting mobile subscribers to the satellite network, ∈₁Is the relevant weighting parameter used to represent the conversion percentage.

A2, based on the determined dynamic change function of the service load of the prey satellite when unloading does not occur, determining the dynamic change function of the service unloading of the prey satellite when the calculation capacity of the prey satellite is lower than the unloading rate of the service load of the prey satellite;

in this example, assume captureSatellite of eater s₂Has a lower computing power than the prey satellite s₁Unloading rate of service load, then predator satellite s₂Load on service with satellite s from prey₁Increasing with the process of unloading service load to predator satellites s₂Off-loading process of, prey satellite s₁The service load of (2) is reduced. Prey satellite s based on Lotka-Volterra model₁The dynamic change in service load can be represented by the following function:

wherein, b₁Representing satellite s from prey₁To predator satellite s₂Of the service load, x₂(t) denotes the predator satellite s at time t₂The service load on the mobile terminal.

A3, re-expressing the dynamic change function of the game satellite service load under the unloading condition according to the internal influence of the satellite group;

in this embodiment, as more and more satellites are used to form the ultra-dense satellite network, the density of satellite nodes in each satellite constellation is a factor that needs to be considered. Prey satellite s₁Dynamic change of service load should consider internal influence of satellite group, based on Lotka-Volterra model, and prey satellite s₁The dynamic change in service load can be restated as follows:

wherein, c₁Representing factors of influence within a satellite constellation, including: resource competition between different satellites within a constellation.

And A4, adding the interference of the external random factors to the dynamic change function of the game satellite service load after the restating to obtain the dynamic change function of the game satellite service load under the interference of the external random factors.

In this embodiment, in the satellite network, due to the influence of the communication environment, the load of each satellite group is inevitably interfered by external random factors, such as cosmic radiation, sun blackness, rainfall attenuation, and the like. It is necessary to add the interference of these external random factors to the prey satellite s₁On the dynamic change of the service load, the following results are obtained:

dx₁(t)＝x₁(t)[a₁(t)-b₁x₂(t)-c₁x₁(t)+ε₁u₁(t)]dt+σ₁(t)x₁(t)dB₁(t) (4)

wherein σ₁(t) a weighting parameter representing interference of an external random factor; b is₁(t) represents the distribution function of the external random factor interference, which generally satisfies the poisson distribution.

In a specific embodiment of the foregoing 6G mobile communication satellite terrestrial network distributed resource allocation method, further constructing a predator satellite service load dynamic change function based on a Lotka-Volterra model includes:

b1, determining a dynamic change function of the service load of the predator satellite when unloading does not occur based on a Lotka-Volterra model;

in this embodiment, at time t, assume that the predator satellite s is₂Service load of x₂(t) if prey satellite s₁On the service load is not offloaded to predator satellites s₂Above, then based on the Lotka-Volterra model, predator satellites s₂The dynamic change function of the service load when no offloading has occurred can be expressed as:

wherein, a₂(t) predator satellites s₂Rate of change of service load, u₂(t) predator satellites s₂The act of attracting mobile subscribers to the satellite network, ∈₂Is the relevant weighting parameter used to represent the conversion percentage.

B2, determining, based on the determined dynamically changing function of the predator satellite service load when no unloading occurs, based on the Lotka-Volterra model, that when the computing power of the predator satellite is lower than the unloading rate of the prey satellite service load, the dynamically changing function of the predator satellite service unloading in the event of unloading is expressed as:

wherein, b₂Representing satellite s from prey₁To predator satellite s₂The rate of increase in service load caused by the offloading process.

B3, according to the internal influence of the satellite group, restating the dynamic change function of the predator satellite service load under the unloading condition;

in this embodiment, predator satellite s₂Dynamic change of service load should consider internal influence of satellite cluster, based on Lotka-Volterra model, predator satellite s₂The dynamic change in service load can be restated as follows:

wherein, c₂Representing factors of influence within the constellation of satellites.

B4, adding the interference of the external random factor to the dynamic change function of the restated predator satellite service load to obtain the dynamic change function of the predator satellite service load under the interference of the external random factor, which is expressed as:

dx₂(t)＝x₂(t)[-a₂(t)+b₂x₁(t)-c₂x₂(t)+ε₂u₂(t)]dt+σ₂(t)x₂(t)dB₂(t) (8)

wherein σ₂(t) a weighting parameter representing interference of an external random factor; b is₂(t) represents the distribution function of the external random factor interference, which generally satisfies the poisson distribution.

In this embodiment, a prey satellite service load dynamic variation function (equation (4)) and a predator satellite service load dynamic variation function (equation (8)) are respectively constructed to describe the load balancing problem among different satellites.

In this embodiment, the existence of uniqueness of the solutions of the equations (4) and (8) is verified according to the random differential equation theory, and specifically, the theorem is verified: for any initial value Representing real numbers, the solution of equation (8) is unique.

And (3) proving that: according to the random differential equation theory, when the coefficients of the equations (4) and (8) satisfy the local Lipschitz condition and the linear growth condition, the solutions of the equations (4) and (8) satisfying the initial value condition are globally unique. Obviously, the coefficients of equations (4) and (8) satisfy the local Lipschitz condition, but do not satisfy the linear growth condition. Therefore, the solutions of equations (4) and (8) tend to be infinite within a finite time.

Since the coefficients of equation (4) and equation (8) satisfy the local Lipschitz condition, the initial condition is givenIn the time interval [0, τ ] of the formulae (4) and (8)_e) With a unique local solution in which_eIndicating the time of explosion.

In this embodiment, only τ needs to be certified_eThe solutions of equations (4) and (8) are global. Note that the forms of the formulae (4) and (8) can be solved for [0, τ ] in the interval_e) Find an analytical solution, i.e., x₁(t)、x₂(t) final solution, expressed as:

wherein s represents time and is an integrated variable; τ is a specific integral value for calculating the current time.

In the present embodiment, x is determined based on₁(t)、x₂And (t) finally solving to achieve load balance between the prey satellite and the predator satellite, and realize effective allocation of communication network resources and stable operation of the 6G mobile communication satellite ground network.

Obviously, x₁(t) > 0 and x₂(t) > 0. To demonstrate the bounciness, the following comparison equation was constructed:

wherein the content of the first and second substances,respectively, represent solutions under bounded conditions.

Wherein the initial conditions areAndthe display solution of equation (11) can be obtained as follows:

according to the comparative theorem of the random differential equation, it can be knownAnd isSince equation (11) is a constant function or a bounded function,anddoes not tend to be infinite within a finite time. Thus τ_eX is infinity₁(t) and x₂(t) does not tend to infinity within a finite time.

In this embodiment, the MATLAB is further used to perform numerical simulation on the load balancing model formed by the equations (4) and (8), verify the validity of the proposed load balancing model, and implement effective allocation of the communication satellite terrestrial network resources.

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.